G
Gérard Verfaillie
Researcher at Community emergency response team
Publications - 62
Citations - 3138
Gérard Verfaillie is an academic researcher from Community emergency response team. The author has contributed to research in topics: Constraint satisfaction problem & Constraint satisfaction. The author has an hindex of 21, co-authored 62 publications receiving 3030 citations.
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Proceedings Article
Valued constraint satisfaction problems: hard and easy problems
TL;DR: A simple algebraic framework is considered, related to Partial Constraint Satisfaction, which subsumes most of these proposals and is used to characterize existing proposals in terms of rationality and computational complexity.
Journal ArticleDOI
Selecting and scheduling observations of agile satellites
TL;DR: In this article, the authors discuss the problem of managing the new generation of Agile Earth Observing Satellites (AEOS) and present different methods which have been investigated in order to solve a simplified version of the complete problem.
Journal ArticleDOI
Semiring-Based CSPs and Valued CSPs: Frameworks, Properties,and Comparison
Stefano Bistarelli,Ugo Montanari,Francesca Rossi,Thomas Schiex,Gérard Verfaillie,Hélène Fargier +5 more
TL;DR: This paper describes and compares two frameworks for constraint solving where classical CSPs, fuzzy C SPs, weighted CSP’s, partial constraint satisfaction, and others can be easily cast.
Proceedings Article
Solution reuse in dynamic constraint satisfaction problems
Gérard Verfaillie,Thomas Schiex +1 more
TL;DR: A method for reusing any previous solution and producing a new one by local changes on the previous one, either from an empty assignment, or from any previous assignment is proposed and how it can be improved using filtering or learning methods, such as forward-checking or nogood-recording.
Proceedings Article
Russian doll search for solving constraint optimization problems
TL;DR: The Russian Doll Search algorithm is introduced, which replaces one search by n successive searches on nested subproblems, records the results of each search and uses them later, when solving larger subpro problems, in order to improve the lower bound on the global valuation of any partial assignment.